person: Person data
In tripaccess: American Travel Behavior and Access Datasets
person R Documentation
Person data
Description
Include disability, mobility, and other demographic categorical and numeric variables.
Usage
person
Format
A data frame with 99564 rows (each row is a person) and 32 columns
- household_id
Household identifier. Use this variable to join the person dataset and the house dataset. Use both this variable and person_id to join the person dataset and the trip dataset.
- person_id
Person identifier. Use both this variable and household_id to join the person dataset and the trip dataset.
- travel_disability
How long the respondent has had a medical condition that makes it difficult to travel outside of home. Values include 6_months_or_less_disability, More_than_6_months_of_disability, Lifelong_disability, and No_disability.
- sex
Sex of the respondent. Values include Male and Female.
- race
Race of the respondent. Values include White, Black, Asian, American Indian, Hawaiian/Pacific Islander, Multiracial, and Other.
- hispanic_ethnicity
Hispanic or Latino origin. Values include Hispanic and Non-Hispanic.
- nativity
Born in United States. Values include Yes and No.
- age
Age of the respondent. Filtered to ages 18 to 61.
- education
Educational attainment. Values include Less than a high school graduate, High school graduate or GED, Some college or associates degree, Bachelor's degree, and Graduate degree or professional degree.
- self_rated_health
Opinion of health. Values include Excellent, Very good, Good, Fair, and Poor.
- employment_status
Primary activity in previous week. Values include Employed and Unemployed.
- household_income
Household income. Values include Under $10,000, $10,000 to $34,999, $35,000 to $74,999, $75,000 to $149,999, and $150,000 and over.
- household_structure
Count of household members. Values include Lives alone and Does not live alone.
- population_density
Category of population density (persons per square mile) in the census block group of the household's home location. Values include 0-99, 100-499, 500-999, 1,000-1,999, 2,000-3,999, 4,000-9,999, 10,000-24,999, and 25,000 and over.
- urban_rural
Household in urban or rural area. Values include Urban and Rural.
- state
Household state. Includes the 50 states and Washington, DC.
- driver_status
Driver status. Values include Drives and Does not drive.
- cane
Does the respondent use a cane to aid their travel?
- manual_wheelchair
Does the respondent use a manual wheelchair to aid their travel?
- crutches
Does the respondent use a crutch to aid their travel?
- dog
Does the respondent use a dog to aid their travel?
- motorized_wheelchair
Does the respondent use a motorized wheelchair to aid their travel?
- scooter
Does the respondent use a scooter to aid their travel?
- white_cane
Does the respondent use a white cane to aid their travel?
- walker
Does the respondent use a walker to aid their travel?
- other_accommodation
Derived from the original W_NONE variable. Indicates whether no listed mobility aid was reported.
- yearly_miles_personally_driven
Miles personally driven in all vehicles. Values range from 0 to 200000.
- count_of_public_transit_usage
Count of public transit usage in last month. Values range from 0 to 30.
- count_of_rideshare_app_usage
Count of rideshare app usage in last month. Values range from 0 to 99.
- count_of_bike_trips
Count of bike trips in past week. Values range from 0 to 99.
- count_of_walk_trips
Count of walk trips in past week. Values range from 0 to 200.
- count_of_online_delivery
Count of times purchased online for delivery in last 30 days. Values range from 0 to 99.
Source
Examples
if (require("tidyverse")) {
# Summary statistics of public transit use by travel disability status
transit_summary <- person |>
group_by(travel_disability) |>
summarize(
people = n(),
public_transit_users = sum(count_of_public_transit_usage > 0),
public_transit_use_prop = mean(count_of_public_transit_usage > 0),
public_transit_usage_median = median(count_of_public_transit_usage),
public_transit_usage_mean = mean(count_of_public_transit_usage),
public_transit_usage_sd = sd(count_of_public_transit_usage)
)
# Test whether public transit use differs by travel disability status
prop.test(
x = transit_summary$public_transit_users,
n = transit_summary$people
)
}
tripaccess documentation built on Aug. 29, 2026, 1:07 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| person | R Documentation |
Person data
Description
Include disability, mobility, and other demographic categorical and numeric variables.
Usage
person
Format
A data frame with 99564 rows (each row is a person) and 32 columns
- household_id
Household identifier. Use this variable to join the person dataset and the house dataset. Use both this variable and person_id to join the person dataset and the trip dataset.
- person_id
Person identifier. Use both this variable and household_id to join the person dataset and the trip dataset.
- travel_disability
How long the respondent has had a medical condition that makes it difficult to travel outside of home. Values include 6_months_or_less_disability, More_than_6_months_of_disability, Lifelong_disability, and No_disability.
- sex
Sex of the respondent. Values include Male and Female.
- race
Race of the respondent. Values include White, Black, Asian, American Indian, Hawaiian/Pacific Islander, Multiracial, and Other.
- hispanic_ethnicity
Hispanic or Latino origin. Values include Hispanic and Non-Hispanic.
- nativity
Born in United States. Values include Yes and No.
- age
Age of the respondent. Filtered to ages 18 to 61.
- education
Educational attainment. Values include Less than a high school graduate, High school graduate or GED, Some college or associates degree, Bachelor's degree, and Graduate degree or professional degree.
- self_rated_health
Opinion of health. Values include Excellent, Very good, Good, Fair, and Poor.
- employment_status
Primary activity in previous week. Values include Employed and Unemployed.
- household_income
Household income. Values include Under $10,000, $10,000 to $34,999, $35,000 to $74,999, $75,000 to $149,999, and $150,000 and over.
- household_structure
Count of household members. Values include Lives alone and Does not live alone.
- population_density
Category of population density (persons per square mile) in the census block group of the household's home location. Values include 0-99, 100-499, 500-999, 1,000-1,999, 2,000-3,999, 4,000-9,999, 10,000-24,999, and 25,000 and over.
- urban_rural
Household in urban or rural area. Values include Urban and Rural.
- state
Household state. Includes the 50 states and Washington, DC.
- driver_status
Driver status. Values include Drives and Does not drive.
- cane
Does the respondent use a cane to aid their travel?
- manual_wheelchair
Does the respondent use a manual wheelchair to aid their travel?
- crutches
Does the respondent use a crutch to aid their travel?
- dog
Does the respondent use a dog to aid their travel?
- motorized_wheelchair
Does the respondent use a motorized wheelchair to aid their travel?
- scooter
Does the respondent use a scooter to aid their travel?
- white_cane
Does the respondent use a white cane to aid their travel?
- walker
Does the respondent use a walker to aid their travel?
- other_accommodation
Derived from the original W_NONE variable. Indicates whether no listed mobility aid was reported.
- yearly_miles_personally_driven
Miles personally driven in all vehicles. Values range from 0 to 200000.
- count_of_public_transit_usage
Count of public transit usage in last month. Values range from 0 to 30.
- count_of_rideshare_app_usage
Count of rideshare app usage in last month. Values range from 0 to 99.
- count_of_bike_trips
Count of bike trips in past week. Values range from 0 to 99.
- count_of_walk_trips
Count of walk trips in past week. Values range from 0 to 200.
- count_of_online_delivery
Count of times purchased online for delivery in last 30 days. Values range from 0 to 99.
Source
Examples
if (require("tidyverse")) {
# Summary statistics of public transit use by travel disability status
transit_summary <- person |>
group_by(travel_disability) |>
summarize(
people = n(),
public_transit_users = sum(count_of_public_transit_usage > 0),
public_transit_use_prop = mean(count_of_public_transit_usage > 0),
public_transit_usage_median = median(count_of_public_transit_usage),
public_transit_usage_mean = mean(count_of_public_transit_usage),
public_transit_usage_sd = sd(count_of_public_transit_usage)
)
# Test whether public transit use differs by travel disability status
prop.test(
x = transit_summary$public_transit_users,
n = transit_summary$people
)
}
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.